从 65,726 个高星开源项目里，
找到你要的下一个。

annotated_deep_learning_paper_implementations 是用 Python 编写的 AI 工具，用于人工智能方向的建模与推理。

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit,…

FinGPT 是用 Jupyter Notebook 编写的学习资料，用于系统学习与查阅，主打开源免费。

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

ml-agents 是用 C# 编写的学习资料，用于系统学习与查阅，主打开源免费。

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for trai…

agent-lightning 是用 Python 编写的 AI 工具，用于大模型与智能体应用开发。

The absolute trainer to light up AI agents.

Book-Mathematical-Foundation-of-Reinforcement-Learning 是用 MATLAB 编写的学习资料，用于系统学习与查阅。

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

tensor2tensor 是用 Python 编写的学习资料，用于系统学习与查阅。

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

awesome-artificial-intelligence 是用 Python 编写的学习资料，用于系统学习与查阅。

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/

强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/

reinforcement-learning-an-introduction 是用 Python 编写的学习资料，用于系统学习与查阅。

Python Implementation of Reinforcement Learning: An Introduction

bullet3 是用 C++ 编写的学习资料，用于系统学习与查阅，主打实时。

Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.

stable-baselines3 是用 Python 编写的学习资料，用于系统学习与查阅，主打适合生产环境。

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Gymnasium 是用 Python 编写的学习资料，用于系统学习与查阅。

A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

amazon-sagemaker-examples 是用 Jupyter Notebook 编写的学习资料，用于系统学习与查阅。

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

ART 是用 Python 编写的 AI 工具，用于大模型与智能体应用开发。

Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning f…

OpenRLHF 是用 Python 编写的学习资料，用于系统学习与查阅，主打高性能、易用、可伸缩。

An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)

Sana 是用 Python 编写的学习资料，用于系统学习与查阅。

SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer

TensorFlow-Tutorials 是用 Jupyter Notebook 编写的学习资料，用于系统学习与查阅。

TensorFlow Tutorials with YouTube Videos

machine_learning_examples 是用 Python 编写的学习资料，用于系统学习与查阅。

A collection of machine learning examples and tutorials.

vowpal_wabbit 是用 C++ 编写的学习资料，用于系统学习与查阅。

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reducti…

pysc2 是用 Python 编写的学习资料，用于系统学习与查阅。

StarCraft II Learning Environment

trax 是用 Python 编写的学习资料，用于系统学习与查阅。

Trax — Deep Learning with Clear Code and Speed

PaLM-rlhf-pytorch 是用 Python 编写的 AI 工具，用于人工智能方向的建模与推理。

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

reef 是用 Python 编写的 AI 工具，用于大模型与智能体应用开发。

Infrastructure for continually self‑improving agents